E. 75% – Explanation
A contingency table can be constructed from the above data, as shown below:
| PE diagnosed | No PE | |
| Test positive | 30 | 5 |
| Test negative | 10 | 55 |
The sensitivity is therefore 30 / (30 + 10) = 75%
Screening test statistics
It would be unusual for a medical exam not to feature a question based around screening test
statistics. The available data should be used to construct a contingency table as below:
TP = true positive; FP = false positive; TN = true negative; FN = false negative
| Disease present | Disease absent | |
| Test positive | TP | FP |
| Test negative | FN | TN |
The table below lists the main statistical terms used in relation to screening tests:
| Sensitivity | TP / (TP + FN ) | Proportion of patients with the condition who have a positive test result |
| Specificity | TN / (TN + FP) | Proportion of patients without the condition who have a negative test result |
| Negative predictive value | TN / (TN + FN) | The chance that the patient does not have the condition if the diagnostic test is negative |
| Likelihood ratio for a positive test result |
sensitivity / (1 – specificity) | How much the odds of the disease increase when a test is positive |
| Likelihood ratio for a negative test result |
(1 – sensitivity) / specificity | How much the odds of the disease decrease when a test is negative |
Positive and negative predictive values are prevalence dependent. Likelihood ratios are not
prevalence dependent
